get_tensor

Retrieve a tensor by record ID.

Server Tensorus MCP tensorus/mcp
Category Read
Risk class Low
Parameters 00 required

What get_tensor does on Tensorus MCP

AI agents call get_tensor to retrieve information from Tensorus MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why get_tensor needs a policy

This tool retrieves data from a tensor database using a record identifier. It performs a query-like operation with no ability to modify, delete, or execute code. The blast radius of misuse is minimal — at worst, an agent could read tensors it shouldn't have access to, which is a confidentiality concern rather than an integrity or operational risk. Severity is low because retrieval alone cannot damage data or systems.

From the tool's definition Tool name is 'get_tensor' and description states 'Retrieve a tensor by record ID' — a pure read operation with no modifications, deletions, or side effects.

Questions about get_tensor

What does the get_tensor tool do? +

Retrieve a tensor by record ID. It is categorised as a Read tool in the Tensorus MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_tensor? +

Register the Tensorus MCP server in PolicyLayer and add a rule for get_tensor: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Tensorus MCP. Nothing to install.

What risk level is get_tensor? +

get_tensor is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_tensor? +

Yes. Add a rate_limit block to the get_tensor rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block get_tensor completely? +

Set action: deny in the PolicyLayer policy for get_tensor. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides get_tensor? +

get_tensor is provided by the Tensorus MCP server (tensorus/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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